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Artificial Intelligence for Irrigation System Optimization: Leveraging Predictive Analytics to Enhance Water Management and Decrease Agricultural Resource Consumption

Artificial Intelligence for Irrigation System Optimization: ...

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Computational, Communication and Information technology (ICCCIT), International Conference on

作者： V.Samuthira Pandi Prashanth Kura Aruna V K.Suresh Kumar D. Nirmala S. Rajesh Kumar Centre for Advanced Wireless Integrated Technology Chennai Institute of Technology Chennai Tamil Nadu India AVS Solutions Inc. 6010 W SPRING PKWY STE 339 PLANO USA Department of Management Studies St.Joseph's Institute of Technology Chennai Tamil Nadu India Department of MBA Panimalar Engineering College Chennai Tamil Nadu India Department of ECE Rajalakshmi Engineering College Chennai Tamil Nadu India Department of CSE(AIML) Sri Sai Ram Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798331512965

ISBN: (纸本)9798331512972

Irrigation system optimization is of utmost importance for sustainable agriculture in light of the growing worldwide water shortage caused by climate change and rising agricultural needs. In order to improve water management techniques and decrease agricultural resource use, this project investigates the use of AI and predictive analytics. An intelligent irrigation system that adapts water distribution in real-time according to predictive analytics is created in this study by combining state-of-the-art machine learning algorithms with real-time data from a variety of sources, such as weather predictions, soil moisture levels, and crop water needs. In order to reduce water waste and maximize irrigation efficiency, the suggested framework uses past data to train artificial intelligence models. Results from field studies on a variety of crops show that water efficiency has been improved, allowing for 30% reductions in irrigation water use without sacrificing or diminishing crop yields. Sustainable farming practices and better resource management are two additional benefits that farmers reap from using AI-driven insights to inform their decision-making. This research emphasizes the revolutionary power of AI to update irrigation methods, leading to more robust agricultural systems. This study highlights the significance of data-driven methods to water management in achieving food security and environmental sustainability through the integration of technology and agriculture. If we want to see optimal irrigation practices adopted all throughout the world, our next step is to improve the predictive models and make the framework function in more diverse agricultural settings.

关键词： Training Irrigation Soil moisture Weather forecasting Predictive models Real-time systems Artificial intelligence Predictive analytics Water resources Optimization

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Thermally stabilized interface structure of the θ′-precipitates in heat-resistant AlCu(ScZr) alloys

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Journal of Alloys and Compounds 2025年 1028卷

作者： Yan, J. Dong, L. Ming, W.Q. Gao, Y.W. Zhao, X.Q. Wu, C.L. Chen, J.H. Center for High-Resolution Electron Microscopy College of Materials Science and Engineering Hunan University Hunan Province Changsha410082 China Innovation Institute for Ocean Materials Characterization Technology State Key Lab of Tropic Ocean Engineering Materials and Materials Evaluation Hainan University Hainan Province Haikou570228 China Key Laboratory of Pico Electron Microscopy of Hainan Province Center for Advanced Studies in Precision Instruments Hainan University Hainan Province Haikou570228 China School of Intelligent Manufacturing and Mechanical Engineering Hunan Institute of Technology Hunan Province Hengyang421000 China

AlCu alloy series are important and interesting heat-resistant materials widely used in aerospace and automotive industry. Up to date, the heat-resistance mechanisms of the alloys are still controversial. Here, we report a thermally stabilized interface structure of θ′-precipitate and propose a new mechanism by which the Sc element enhance thermal stability of the alloys. By utilizing state-of-the-art electron microscopy and elemental atomic-resolution imaging, it is shown that GP zones and θ′′ precipitates, which form during a preliminary low-temperature aging, do not transform into the θ′-precipitates. Instead, they rapidly dissolve upon subsequent thermal exposure at 300 °C, thereby accelerating the early formation and coarsening of θ′ and θ precipitates, ultimately reducing the heat resistance of alloys. On the contrary, the formation of Sc/θ′/Sc or Al3Sc/θ′/Al3Sc composite precipitates in the alloys via a high-temperature aging process results in the thermally stabilization of all interfaces of the strengthening θ′-precipitates, which greatly improve the heat resistance of Al-Cu alloys. There exists either an "in-phase" or an "anti-phase" relationship between the two sideward Al3Sc layers within these Al3Sc/θ′/Al3Sc composite precipitates, which is determined exclusively by the number of Cu-layers in the central θ′-precipitate. This unique interface configuration necessitates the realignment of all Sc atoms in each Sc-containing layer whenever the θ′ precipitate increases in thickness by one Cu-layer. This mechanism effectively inhibits rapid thickening of θ′-precipitates at elevated temperatures. Our findings offer atomic-scale insights into the heat-resistant properties and optimal thermal processing of the alloys. © 2025 Elsevier B.V.

关键词： High resolution electron microscopy

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Critical role of vegetation and human activity indicators in the prediction of shallow groundwater quality distribution in Jianghan Plain with LightGBM algorithm and SHAP analysis

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Chemosphere 2025年 376卷 144278页

作者： Xiong, Hanxiang Wang, Jinghan Yang, Chi Li, Shuyi Li, Xiaobo Xiong, Ruihan Wang, Yuzhou Ma, Chuanming School of Environmental Studies China University of Geosciences Wuhan430074 China School of Energy Science and Engineering Central South University Changsha410083 China Shandong Fifth Institute of Geology and Mineral Exploration Tai'an250013 China State Key Laboratory of Geomicrobiology and Environmental Changes China University of Geosciences Wuhan430078 China Eastern Institute for Advanced Study Eastern Institute of Technology Ningbo315200 China School of Environmental Science and Engineering Shanghai Jiao Tong University Shanghai200240 China

Groundwater serves as an indispensable resource for freshwater, but its quality has experienced a notable decline over recent decades. Spatial prediction of groundwater quality (GWQ) can effectively assist managers in groundwater remediation, management, and risk control. Based on the traditional intrinsic groundwater vulnerability (IGV) model (DRASTIC) and three vegetation (V) indicators (NDVI, EVI, and kNDVI) and four human activity (H) indicators (land use, GDP, urbanization index, and nighttime light), we constructed four models for GWQ spatial prediction in the Jianghan Plain (JHP), namely DRASTI, DRASTIH, DRASTIV, and DRASTIVH, excluding the conductivity (C) indicator due to its uniformly low values. LightGBM algorithm, Tree-structured Parzen Estimator (TPE) optimization method, and SHapley Additive exPlanations (SHAP) analysis are used for model setting, calibration, and interpretation, respectively. The results show that nitrogen-related GWQ parameters have higher weights, and the model performs exceptionally well when considering all the indicators (accuracy = 0.840, precision = 0.824, recall = 0.832, F1 score = 0.828, AUROC = 0.914). Notably, the introduced indicators (NDVI, EVI, kNDVI, nighttime light, GDP, and urbanization index) rank as the top six in terms of importance, while traditional DRASTI and land use indicators show lower significance. Based on SHAP analysis, poor GWQ primarily occurs in areas with either extremely high or extremely low GDP and urbanization index values, and human activities are the primary cause of poor GWQ in JHP, potentially involving urbanization, industrial and agricultural activities, as well as fertilizer usage. Finally, the methodological framework proposed in this study is encouraged to be applied to diverse regions, such as plains, karst areas, mountainous regions, and coastal areas, to support effective future groundwater management. © 2025 Elsevier Ltd

关键词： Quality management

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Unveiling intracavity soliton evolution dynamics of a mode-locked fiber laser along the dispersion map

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Photonics Research 2025年第5期13卷 1130-1136页

作者： Zhang, Jiarun Lu, Tianchang Yao, Xiankun Zhang, Yusheng Mao, Dong Zeng, Chao Hao, Xiang Tang, Longhua Cui, Yudong Kuang, Cuifang Liu, Xu State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and Engineering Zhejiang University Hangzhou310027 China School of Physics Northwest University Xi’an710127 China Key Laboratory of Light Field Manipulation and Information Acquisition Ministry of Industry and Information Technology School of Physical Science and Technology Northwestern Polytechnical University Xi’an710129 China Hangzhou Institute of Advanced Studies Zhejiang Normal University Hangzhou311231 China ZJU-Hangzhou Global Scientific and Technological Innovation Center Hangzhou311200 China

Mode-locked fiber lasers are excellent platforms for soliton generation. Solitons exhibit distinct distribution and evolution characteristics depending on the net dispersion of the laser cavity. Here we propose an experimental scheme to reconstruct the intracavity dynamics of solitons within a mode-locked fiber laser. The proposed scheme is facilitated by disposing multiple output ports at different positions throughout the cavity, thereby enabling in-depth observation and manipulation of soliton evolution along the dispersion map. The experimental results verify corresponding simulations and explain some phenomena from the perspective of soliton evolution. Our results offer a pathway for comprehensive analyses of intracavity pulse dynamics, fostering advancements in nonlinear and ultrafast optics. © 2025 Chinese Laser Press.

关键词： Nonlinear optics

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Deep Learning and IoT Based Robotics to Monitor the Traffic 2nd

Deep Learning and IoT Based Robotics to Monitor the Traffic

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2nd International Conference on Cyber Warfare, Security and Space Computing, SpacSec 2024

作者： Priya, V. Vishwa Pande, Soumitra S. Ilyas, Md Jayasudha, R. Ramesh, Janjhyam Venkata Naga Suganthi, D. Department of Computer Science Vels Institute of Science Technology and Advanced Studies Chennai India Ericsson Global India Private Limited Bangalore India Prestige Institute of Engineering Management and Research Indore India Dr. N. G. P. Institute of Technology Coimbatore India Koneru Lakshmaiah Education Foundation Andhra Pradesh Guntur Vaddeswaram India Saveetha College of Liberal Arts and Sciences SIMATS Thandalam Chennai India

ISBN: (纸本)9783031734939

In densely populated areas, managing traffic laws has become more difficult due to the rising number of cars on the road. One of the most critical components of effective traffic management and improved mobility is real-time traffic monitoring systems. Consequently, precise and dependable real-time traffic information has always been essential for cars and drivers. Many other approaches have been suggested as potential answers to the issues plaguing traffic conditions recently. A different approach is VCC or vehicle cloud computing. In addition, an advanced model called an Iot-aided robotic (IoRT), which uses cameras and Internet of Things (IoT) detector nodes to gather actual traffic information, has been created. Two deep learning methods, one based on improved LeNet-5 for real-time signs for traffic identification and the other on the Inception-V3 model for detecting and identifying traffic lights, are the critical contributions provided by this research effort. Additionally, to decrease road accidents, the ideal distance between barriers and ultrasonic sensors was determined by analyzing the timing and speed of ultrasonic waves. Data acquired by cameras and sensors is analyzed using a variety of image processing algorithms before being uploaded to the cloud and made accessible to commuters and drivers via a mobile app. According to the test findings, the suggested models are far more accurate. The expanded GTSRB (EGTSRB) dataset achieved 98.89% accuracy while the German Traffic Sign Recognition Benchmark (GTSRB) dataset achieved 98.23% accuracy using the modified LeNet-5. The second model achieved a precision of 99.7 percent using data from the Laboratory for the Intelligent and Safe Automobiles (LISA). The results of this study beat previous research on comparable traffic monitoring systems by 2.13% for traffic light recognition and detection and by 4.89% for traffic sign identification. © The Author(s), under exclusive license to Springer Nature Switzerland AG

关键词： Traffic signs

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Real-Time GPS Tracking and Health Monitoring for Animals Using IoT and Mobile Application

Real-Time GPS Tracking and Health Monitoring for Animals Usi...

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Machine Learning and Autonomous Systems (ICMLAS), International Conference on

作者： V. Usha Sandeep Karagatla P. Sheela Gowr P.M.G Jegathambal A. Lizy V. Sathya Dept. of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Dept. of CSE (AI&DS) Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Vels Institute of Science Technology & Advanced Studies Chennai Dept. of Artificial Intelligence and Machine Learning Vel Tech Rangarajan Dr. Sagunthala (R&D) Institute of Science and Technology Chennai India Dept of Information Technology Velammal Engineering College Chennai India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

The Internet of Things (IoT) grounded solution of Real Time Global Positioning System (GPS) tracking with Health Monitoring of Animals for Owners to track their animals like cows, buffaloes, dogs etc. This GPS module and a heartbeat sensor are attached to the animals in order to be able to follow them closely. This data is sent to a mobile app, and the owner can see their heart on the map as well as monitor its pulse. Based on analysis of such heart rate variations, the system determines when it is seeing an abnormal activity related to e.g. stress (increased heart rate) or potential health risks (no sign of a heartbeat), which could be interpreted as fear or death. Each animal has an initial heart rate level that is set, and when this rate exceeds it, the system sounds an alert to indicate danger. This method is especially helpful for keeping an eye on animals in urban areas, areas close to forests, and areas with high rates of theft and loss. The project demonstrates the successful execution of a reliable, real-time animal monitoring system with practical applications in both urban and rural environments.

关键词： Animals Tracking Heart beat LoRa Real-time systems Mobile applications Safety Internet of Things Monitoring Global Positioning System

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Exploring the energy landscape of aluminas through machine learning interatomic potential

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Physical Review Materials 2025年第2期9卷 023801-023801页

作者： Lei Zhang Wenhao Luo Renxi Liu Mohan Chen Zhongbo Yan Kun Cao Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices State Key Laboratory of Optoelectronic Materials and Technologies Center for Neutron Science and Technology School of Physics Sun Yat-Sen University Guangzhou 510275 China HEDPS CAPT College of Engineering Peking University Beijing 100871 China Academy for Advanced Interdisciplinary Studies Peking University Beijing 90871 China AI for Science Institute Beijing 100080 China

Aluminum oxide (alumina, Al2O3) exists in various structures and has broad industrial applications. While the crystal structure of α−Al2O3 is well-established, those of transitional aluminas remain highly debated. In this study, we propose a universal machine learning interatomic potential (MLIP) for aluminas, trained using the neuroevolution potential (NEP) approach. The dataset is constructed through iterative training and farthest point sampling, ensuring the generation of the most representative configurations for an exhaustive sampling of the potential energy surface. The accuracy and generality of the potential are validated through simulations under a wide range of conditions, including high temperatures and pressures. A phase diagram is presented that includes both transitional aluminas and α−Al2O3 based on the NEP. We also successfully extrapolate the phase diagram of aluminas under extreme conditions ([0, 4000] K and [0, 200] GPa ranges of temperature and pressure, respectively), while maintaining high accuracy in describing their properties under more moderate conditions. Furthermore, combined with our developed structure search workflow, the NEP provides an evaluation of existing γ−Al2O3 structure models. The NEP developed in this work enables highly accurate dynamic simulations of various aluminas on larger scales and longer timescales, while also offering new insights into the study of transitional aluminas structures.

关键词： Aluminum oxide

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A review on characteristics and synergistic behaviour of coal-biomass blends in co-pyrolysis process for bioenergy generation

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Carbon Letters 2025年 1-40页

作者： Khoja, Asif Hussain Hussain, Muzzamail Tauseef, Maham Naeem, Nida Khan, Arslan Akram, Ramza Khan, Tahreem Assad Ansari, Abeera Ayaz Zeng, Xi U.S.-Pakistan Centre for Advanced Studies in Energy (USPCAS-E) National University of Sciences and Technology (NUST) Sector H-12 Islamabad 44000 Pakistan Department of Chemical and Environmental Engineering (ChEE) University of Cincinnati Cincinnati 45221-0012 OH United States State Key Laboratory of Multi-Phase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing 100190 China Laboratory of Alternative Fuels and Sustainability School of Chemical and Materials Engineering National University of Sciences and Technology Islamabad 44000 H-12 Pakistan School of Interdisciplinary Engineering and Science (SINES) National University of Sciences and Technology (NUST) Sector H-12 Islamabad 44000 Pakistan School of Ecology and Environment Beijing Technology and Business University Beijing 100048 China

The environmental, social, and economic concerns regarding fossil fuels necessitate the demand for an efficient energy mix utilising renewable resources like biomass for sustainable development. Recent interest in the thermochemical conversion of coal and biomass into bioenergy via co-pyrolysis processes is gaining importance. This review critically assesses the behaviour of different types of coal and biomass blends during co-pyrolysis from various perspectives, including the effects of temperature, blending ratios, heating rate, synergistic and inhibitive behaviours, heat transfer mechanisms, nature of products, and their future applications. The possible synergies arising due to differences in the compositions of coal and biomass are discussed. In addition, the synergistic effect on co-pyrolysis yield is critically presented. Moreover, it is analysed that the co-pyrolysis offers higher yields of liquid and gaseous fuels compared to individual feedstock coal and biomass. Co-pyrolysis of coal and biomass can be promoted from a scientific standpoint;however, further research is still required for the integration of new technologies to enhance the effectiveness of co-pyrolysis. © The Author(s), under exclusive licence to Korean Carbon Society 2025.

关键词： Bio-oil Blending ratios Char Co-pyrolysis Gases Synergy Temperature

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Development of Antimicrobial Peptide-loaded Hydrogels as Potential Scaffolds for Pulp-dentine Complex Regeneration: A Comparative Study

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Journal of Endodontics 2025年第5期51卷 585-593页

作者： Noohi, Parisa Abdekhodaie, Mohammad J. Nekoofar, Mohammad H. Gama, Miguel Saadatmand, Maryam Dummer, Paul M.H. Department of Chemical and Petroleum Engineering Sharif University of Technology Tehran Tehran Iran Discovery and Translational Sciences Department Leeds Institute of Cardiovascular and Metabolic Medicine School of Medicine University of Leeds West Yorkshire Leeds United Kingdom Environmental and Applied Science Management Yeates School of Graduate Studies Toronto Metropolitan University Toronto ON Canada Department of Endodontics School of Dentistry Tehran University of Medical Sciences Tehran Tehran Iran Department of Tissue Engineering School of Advanced Technologies in Medicine Tehran University of Medical Sciences Tehran Tehran Iran Department of Endodontics Bahçeşehir University School of Dentistry Istanbul Istanbul Türkiye Centre of Biological Engineering University of Minho Minho Braga Portugal School of Dentistry College of Biomedical and Life Sciences Cardiff University Wales Cardiff United Kingdom

Introduction: As a recently developed treatment modality, regeneration of the pulp-dentin-like complex via tissue engineering approaches is the focus of considerable attention. The persistence of bacteria within the root canal spaces is well known as the major challenge of dental pulp regeneration. Antimicrobial peptides (AMPs) are short peptides with inhibitory activities against a broad spectrum of microorganisms. Methods: In the present study, antimicrobial hydrogels based on 2 photo-reactive biopolymers, that is collagen methacrylate and chitosan methacrylate, and containing 2 different AMPs, that is LLKKK18 and Tet213, were used to develop a potential scaffold with antimicrobial and regenerative features. Results: The incorporation of AMPs had no significant effect on the physical, mechanical, rheological, and morphological properties of the new systems. The optimized concentration of LLKKK18 and Tet213 had appropriate antimicrobial activity against Gram-positive Enterococcus fæcalis and did not exhibit any cytotoxicity to stem cells from the apical papilla encapsulated within the hydrogels compared to the control group without AMPs. The presence of AMPs also significantly promoted migration and differentiation of stem cells from the apical papilla. In the AMP-loaded groups, greater levels of calcified nodules deposition, alkaline phosphatase, collagen type I, dentin sialophosphoprotein, dentin matrix protein 1, and vascular endothelial growth factor A mRNA gene expression, and collagen type I and dentin sialophosphoprotein protein expression were observed. Conclusions: The results indicated the potential of engineered antimicrobial collagen methacrylate/chitosan methacrylate hydrogels for application in tissue engineering-based strategies to regenerate the pulp-dentin complex. © 2025 American Association of Endodontists

关键词： Antimicrobial peptides chitosan methacrylate collagen methacrylate photo-crosslinking regenerative endodontics

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Mathematical Modeling of Thin Layer Drying Kinetics of Apple in Tunnel Dryer

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INTERNATIONAL JOURNAL OF FOOD engineering 2008年第8期4卷 8/1-8/16页

作者： Goyal, Raj Kumar Mujjeb, O. Bhargava, Vinod Kumar Central Institute of Post Harvest Engineering and Technology Mar Athanasios College For Advanced Studies Tiruvalla

In this study, the drying kinetics of apple (control, blanching and blanching in 1% potassium meta bisulphate) in a tunnel dryer was studied at 50, 60, and 70 degrees C air temperatures. The drying of apple slices occurred in a falling rate period. It was found that treated apple slices dried faster. Six thin layer-drying models were fitted to the experimental moisture ratio. Among the mathematical models evaluated, the logarithmic model satisfactorily described the drying behaviour of apple slices with high r2 values. The effective moisture diffusivity (Deff) of apple slices increased as the drying air temperature increased. The Deff values were higher for the treated samples than for the control.

关键词： apple diffusivity drying mathematical models tunnel dryer

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